GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]

Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

[KDD'2023] "KGRec: Knowledge Graph Self-Supervised Rationalization for Recommendation"

[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization

Tools for exploiting Morphological Symmetries in robotics

Ratioanle-aware Graph Contrastive Learning codebase

[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization

This repo contains code for Invariant Grounding for Video Question Answering

[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

Causal Disentangled Recommendation Against Preference Shifts (TOIS), 2023

[ICML'24W] Revisiting Random Walks for Learning on Graphs, in PyTorch

Code for "Environment Diversification with Multi-head Neural Network for Invariant Learning" (NeurIPS 2022)

DELA - Disentanglement Learning Archive

Basic Invariant Test Practice in Foundry